In [ ]:
###Identify genes with cell type specific expression in a cell type of interest
###Uses data from the Tabula muris - a multi tissue atlas
###This example identifies high and specifically expressed genes in type B pancreatic cells
In [1]:
import scanpy
import pandas as pd
import numpy as np
import igraph
import sys
import pooch
import matplotlib as plt
import anndata as ad
import leidenalg
import seaborn as sns
In [2]:
print(sys.version)
scanpy.logging.print_versions()
3.11.11 | packaged by Anaconda, Inc. | (main, Dec 11 2024, 16:34:19) [MSC v.1929 64 bit (AMD64)] ----- anndata 0.11.1 scanpy 1.10.4 ----- PIL 11.0.0 anyio NA asttokens NA attr 24.2.0 attrs 24.2.0 babel 2.11.0 backports NA brotli 1.0.9 certifi 2024.08.30 charset_normalizer 3.3.2 colorama 0.4.6 comm 0.2.1 cycler 0.12.1 cython_runtime NA dateutil 2.9.0.post0 debugpy 1.6.7 decorator 5.1.1 defusedxml 0.7.1 executing 0.8.3 fastjsonschema NA h5py 3.12.1 idna 3.7 igraph 0.11.8 ipykernel 6.29.5 jaraco NA jedi 0.19.2 jinja2 3.1.4 joblib 1.4.2 json5 0.9.25 jsonschema 4.23.0 jsonschema_specifications NA jupyter_events 0.10.0 jupyter_server 2.14.1 jupyterlab_server 2.27.3 kiwisolver 1.4.7 legacy_api_wrap NA leidenalg 0.10.2 llvmlite 0.43.0 markupsafe 2.1.3 matplotlib 3.10.0 more_itertools 10.3.0 mpl_toolkits NA natsort 8.4.0 nbformat 5.10.4 nt NA numba 0.60.0 numpy 2.0.2 overrides NA packaging 24.1 pandas 2.2.3 parso 0.8.4 patsy 1.0.1 pkg_resources NA platformdirs 3.10.0 pooch v1.8.2 prometheus_client NA prompt_toolkit 3.0.43 psutil 5.9.0 pure_eval 0.2.2 pydev_ipython NA pydevconsole NA pydevd 2.9.5 pydevd_file_utils NA pydevd_plugins NA pydevd_tracing NA pygments 2.15.1 pyparsing 3.2.0 pythoncom NA pythonjsonlogger NA pytz 2024.1 pywintypes NA referencing NA requests 2.32.3 rfc3339_validator 0.1.4 rfc3986_validator 0.1.1 rpds NA scipy 1.14.1 seaborn 0.13.2 send2trash NA session_info 1.0.0 six 1.16.0 sklearn 1.6.0 sniffio 1.3.0 socks 1.7.1 stack_data 0.2.0 statsmodels 0.14.4 texttable 1.7.0 threadpoolctl 3.5.0 tornado 6.4.2 tqdm 4.67.1 traitlets 5.14.3 typing_extensions NA urllib3 2.2.3 wcwidth 0.2.5 websocket 1.8.0 win32api NA win32com NA win32con NA win32trace NA winerror NA yaml 6.0.2 zmq 25.1.2 zoneinfo NA ----- IPython 8.27.0 jupyter_client 8.6.0 jupyter_core 5.7.2 jupyterlab 4.2.5 notebook 7.2.2 ----- Python 3.11.11 | packaged by Anaconda, Inc. | (main, Dec 11 2024, 16:34:19) [MSC v.1929 64 bit (AMD64)] Windows-10-10.0.26100-SP0 ----- Session information updated at 2024-12-17 12:53
In [3]:
#Read Tabula muris file
file = "C:/Users/Nilima/Downloads/Tabula_muris.h5ad"
tm = scanpy.read_h5ad(file, backed=None)
In [4]:
#Visualize umaps for tabula muris data
scanpy.pl.umap(tm, color=['donor_id'], show = False)
Out[4]:
<Axes: title={'center': 'donor_id'}, xlabel='UMAP1', ylabel='UMAP2'>
In [5]:
scanpy.pl.umap(tm, color=['tissue'], show = False)
Out[5]:
<Axes: title={'center': 'tissue'}, xlabel='UMAP1', ylabel='UMAP2'>
In [6]:
#Adding a color palette because cell_type_color in uns in just one color
scanpy.pl.umap(tm, color=['cell_type'], show = False, palette=sns.color_palette("husl", 122))
Out[6]:
<Axes: title={'center': 'cell_type'}, xlabel='UMAP1', ylabel='UMAP2'>
In [7]:
scanpy.pl.umap(tm, color=['age'], show = False)
Out[7]:
<Axes: title={'center': 'age'}, xlabel='UMAP1', ylabel='UMAP2'>
In [8]:
scanpy.pl.umap(tm, color=['leiden'], show = False)
Out[8]:
<Axes: title={'center': 'leiden'}, xlabel='UMAP1', ylabel='UMAP2'>
In [9]:
##Subset out data from only old mice i.e age 18m and above
tm_age = tm[tm.obs['age'].isin(['18m','21m','24m','30m'])] #173807
tm_age
Out[9]:
View of AnnData object with n_obs × n_vars = 173807 × 17984
obs: 'age', 'cell', 'free_annotation', 'method', 'donor_id', 'n_genes', 'subtissue', 'tissue_free_annotation', 'n_counts', 'louvain', 'leiden', 'assay_ontology_term_id', 'disease_ontology_term_id', 'cell_type_ontology_term_id', 'tissue_ontology_term_id', 'development_stage_ontology_term_id', 'self_reported_ethnicity_ontology_term_id', 'sex_ontology_term_id', 'is_primary_data', 'organism_ontology_term_id', 'suspension_type', 'tissue_type', 'cell_type', 'assay', 'disease', 'organism', 'sex', 'tissue', 'self_reported_ethnicity', 'development_stage', 'observation_joinid'
var: 'n_cells', 'means', 'dispersions', 'dispersions_norm', 'highly_variable', 'feature_is_filtered', 'feature_name', 'feature_reference', 'feature_biotype', 'feature_length', 'feature_type'
uns: 'age_colors', 'citation', 'leiden', 'louvain', 'louvain_colors', 'neighbors', 'pca', 'schema_reference', 'schema_version', 'title', 'donor_id_colors', 'tissue_colors', 'cell_type_colors', 'leiden_colors'
obsm: 'X_pca', 'X_umap'
varm: 'PCs'
obsp: 'connectivities', 'distances'
In [10]:
#Check what data in X looks like
print(tm_age.X)
#Data looks lognormalized
<Compressed Sparse Row sparse matrix of dtype 'float32' with 318314973 stored elements and shape (173807, 17984)> Coords Values (0, 0) 2.510500192642212 (0, 3) 2.1507961750030518 (0, 7) 2.32142972946167 (0, 61) 3.3847835063934326 (0, 62) 2.9239156246185303 (0, 64) 9.102213859558105 (0, 78) 4.178806304931641 (0, 94) 2.3215222358703613 (0, 122) 4.577788829803467 (0, 123) 2.8975045680999756 (0, 136) 6.1979780197143555 (0, 170) 6.624351978302002 (0, 171) 2.3061585426330566 (0, 174) 3.457357883453369 (0, 192) 6.093574047088623 (0, 196) 4.185334205627441 (0, 197) 2.5703203678131104 (0, 202) 2.872211217880249 (0, 207) 2.9703168869018555 (0, 210) 2.825045585632324 (0, 212) 5.69992208480835 (0, 218) 3.5929737091064453 (0, 223) 2.658627510070801 (0, 235) 6.694092273712158 (0, 259) 2.047475576400757 : : (173806, 17843) 1.8416699171066284 (173806, 17866) 3.0298855304718018 (173806, 17874) 1.3424092531204224 (173806, 17877) 2.0523200035095215 (173806, 17879) 1.9859824180603027 (173806, 17884) 2.946965217590332 (173806, 17899) 0.9775243997573853 (173806, 17907) 3.577437162399292 (173806, 17911) 2.4104104042053223 (173806, 17914) 4.130761623382568 (173806, 17917) 3.093820571899414 (173806, 17918) 2.4857301712036133 (173806, 17921) 1.7679980993270874 (173806, 17927) 1.0614545345306396 (173806, 17931) 2.722872495651245 (173806, 17932) 1.5297518968582153 (173806, 17937) 2.930830717086792 (173806, 17940) 2.0788960456848145 (173806, 17945) 2.092453718185425 (173806, 17963) 0.9995285272598267 (173806, 17964) 1.426791787147522 (173806, 17966) 1.8350032567977905 (173806, 17970) 1.8489338159561157 (173806, 17975) 1.3724377155303955 (173806, 17979) 3.4143760204315186
In [11]:
tm_age.layers["counts"]= tm_age.X.copy()
tm_age.to_df(layer= 'counts')
C:\Users\Nilima\AppData\Local\Temp\ipykernel_26324\1069023437.py:1: ImplicitModificationWarning: Setting element `.layers['counts']` of view, initializing view as actual. tm_age.layers["counts"]= tm_age.X.copy()
Out[11]:
| ENSMUSG00000029422 | ENSMUSG00000049036 | ENSMUSG00000029577 | ENSMUSG00000040746 | ENSMUSG00000020590 | ENSMUSG00000030263 | ENSMUSG00000038914 | ENSMUSG00000026878 | ENSMUSG00000038984 | ENSMUSG00000030098 | ... | ENSMUSG00000092086 | ENSMUSG00000036257 | ENSMUSG00000057236 | ENSMUSG00000044083 | ENSMUSG00000035875 | ENSMUSG00000020070 | ENSMUSG00000030178 | ENSMUSG00000021033 | ENSMUSG00000030657 | ENSMUSG00000040693 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||
| AAACCTGCAGGGTACA-1-0-0-0 | 2.510500 | 0.0 | 0.000000 | 2.150796 | 0.00000 | 0.000000 | 0.000000 | 2.321430 | 0.0 | 0.0 | ... | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 9.149252 | 0.0 |
| AAACCTGCAGTAAGCG-1-0-0-0 | 1.411730 | 0.0 | 0.000000 | 0.780522 | 0.00000 | 0.000000 | 0.000000 | 1.995112 | 0.0 | 0.0 | ... | 0.0 | 0.886421 | 1.092871 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 |
| AAACCTGTCATTATCC-1-0-0-0 | 1.060576 | 0.0 | 0.000000 | 0.000000 | 0.00000 | 0.000000 | 1.858372 | 2.323704 | 0.0 | 0.0 | ... | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 |
| AAACGGGGTACAGTGG-1-0-0-0 | 0.644871 | 0.0 | 0.000000 | 1.857837 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | ... | 0.0 | 0.928572 | 0.663815 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 |
| AAACGGGGTCTTCTCG-1-0-0-0 | 1.527815 | 0.0 | 0.000000 | 1.937129 | 0.00000 | 0.000000 | 0.000000 | 0.865817 | 0.0 | 0.0 | ... | 0.0 | 0.000000 | 2.018775 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| TTTGGTTCAAGCGTAG-1-40-1-0 | 0.659375 | 0.0 | 0.000000 | 0.836027 | 0.00000 | 0.000000 | 0.000000 | 1.886559 | 0.0 | 0.0 | ... | 0.0 | 0.000000 | 0.678745 | 0.0 | 0.0 | 0.000000 | 0.0 | 4.109947 | 0.000000 | 0.0 |
| TTTGGTTCAATGGACG-1-40-1-0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 2.60133 | 0.000000 | 0.000000 | 2.248132 | 0.0 | 0.0 | ... | 0.0 | 2.994735 | 1.041076 | 0.0 | 0.0 | 0.000000 | 0.0 | 4.562962 | 0.000000 | 0.0 |
| TTTGGTTGTGCTAGCC-1-40-1-0 | 1.197928 | 0.0 | 0.000000 | 0.895619 | 0.00000 | 0.000000 | 0.000000 | 1.456655 | 0.0 | 0.0 | ... | 0.0 | 2.709450 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 4.290936 | 0.000000 | 0.0 |
| TTTGTCAAGGCTCATT-1-40-1-0 | 0.000000 | 0.0 | 2.850029 | 0.000000 | 0.00000 | 0.000000 | 2.923881 | 1.180550 | 0.0 | 0.0 | ... | 0.0 | 1.838365 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 5.057412 | 0.000000 | 0.0 |
| TTTGTCAGTTCGTCTC-1-40-1-0 | 0.953125 | 0.0 | 0.000000 | 0.000000 | 0.00000 | 1.285097 | 0.000000 | 0.881344 | 0.0 | 0.0 | ... | 0.0 | 1.372438 | 0.000000 | 0.0 | 0.0 | 3.414376 | 0.0 | 0.000000 | 0.000000 | 0.0 |
173807 rows × 17984 columns
In [12]:
#Data already normalized+logarithmized - Run this cell only if data is raw
#Normalizing to median total counts
#scanpy.pp.normalize_total(tm_age)
#Logarithmize the data
#scanpy.pp.log1p(tm_age)
#print('done')
In [13]:
#Get only highly variable genes
#scanpy.pp.highly_variable_genes(tm_age,flavor='seurat',batch_key = "tissue")
#scanpy.pl.highly_variable_genes(tm_age)
#tm_age_1 = tm_age[:, tm_age.var["highly_variable"]]
#tm_age_1.shape
#Skipping this step. Clustering looks worse across tissues for this dataset with only highly variable genes
In [14]:
scanpy.pp.pca(tm_age)
In [15]:
#Calculate nearest neighbour distance matrix
scanpy.pp.neighbors(tm_age)
tm_age
C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html from .autonotebook import tqdm as notebook_tqdm
Out[15]:
AnnData object with n_obs × n_vars = 173807 × 17984
obs: 'age', 'cell', 'free_annotation', 'method', 'donor_id', 'n_genes', 'subtissue', 'tissue_free_annotation', 'n_counts', 'louvain', 'leiden', 'assay_ontology_term_id', 'disease_ontology_term_id', 'cell_type_ontology_term_id', 'tissue_ontology_term_id', 'development_stage_ontology_term_id', 'self_reported_ethnicity_ontology_term_id', 'sex_ontology_term_id', 'is_primary_data', 'organism_ontology_term_id', 'suspension_type', 'tissue_type', 'cell_type', 'assay', 'disease', 'organism', 'sex', 'tissue', 'self_reported_ethnicity', 'development_stage', 'observation_joinid'
var: 'n_cells', 'means', 'dispersions', 'dispersions_norm', 'highly_variable', 'feature_is_filtered', 'feature_name', 'feature_reference', 'feature_biotype', 'feature_length', 'feature_type'
uns: 'age_colors', 'citation', 'leiden', 'louvain', 'louvain_colors', 'neighbors', 'pca', 'schema_reference', 'schema_version', 'title', 'donor_id_colors', 'tissue_colors', 'cell_type_colors', 'leiden_colors'
obsm: 'X_pca', 'X_umap'
varm: 'PCs'
layers: 'counts'
obsp: 'connectivities', 'distances'
In [16]:
#UMAP
scanpy.tl.umap(tm_age)
scanpy.pl.umap(tm_age,color='tissue',size=2)
In [17]:
scanpy.pl.umap(tm_age,color='cell_type',size=2)
In [18]:
#Leiden clustering
scanpy.tl.leiden(tm_age, n_iterations=10, key_added = "leiden_res0_25", resolution=0.25)
scanpy.tl.leiden(tm_age, n_iterations=10, key_added = "leiden_res0_5", resolution=0.5)
scanpy.tl.leiden(tm_age, n_iterations=10, key_added = "leiden_res1", resolution=1.0)
#Did not use flavor ="igraph" as there is a current windows specific bug. Change in future iterations
C:\Users\Nilima\AppData\Local\Temp\ipykernel_26324\947233372.py:2: FutureWarning: In the future, the default backend for leiden will be igraph instead of leidenalg. To achieve the future defaults please pass: flavor="igraph" and n_iterations=2. directed must also be False to work with igraph's implementation. scanpy.tl.leiden(tm_age, n_iterations=10, key_added = "leiden_res0_25", resolution=0.25)
In [19]:
#Visualize Leiden clustering
scanpy.pl.umap(tm_age,color=["leiden_res0_25","leiden_res0_5","leiden_res1"], legend_loc="on data")
scanpy.pl.umap(tm_age,color=["cell_type"])
#res1 matches cell_type most closely
In [20]:
#Pick leiden res1 as it matches most closely with cell type
scanpy.pl.umap(tm_age,color=["leiden_res1"], legend_loc="on data")
scanpy.pl.umap(tm_age,color=["cell_type"])
In [21]:
##Find markers - grouping by cell type annotation. Grouping can also be by leiden clustering
scanpy.tl.rank_genes_groups(tm_age, groupby = "cell_type", method ='t-test', use_raw=False)
scanpy.pl.rank_genes_groups(tm_age, n_genes =25, sharey = False)
C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2( C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:429: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "names"] = self.var_names[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:431: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "scores"] = scores[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:434: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals"] = pvals[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:444: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "pvals_adj"] = pvals_adj[global_indices] C:\Users\Nilima\anaconda3\envs\scRNA-seq\Lib\site-packages\scanpy\tools\_rank_genes_groups.py:455: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()` self.stats[group_name, "logfoldchanges"] = np.log2(
In [22]:
#Extract differential expression genes for the cell type of interest
#In this example it is the type B pancreatic cell
mdf = scanpy.get.rank_genes_groups_df(tm_age, group = "type B pancreatic cell")
mdf
Out[22]:
| names | scores | logfoldchanges | pvals | pvals_adj | |
|---|---|---|---|---|---|
| 0 | ENSMUSG00000000215 | 1239.574463 | 16.262800 | 0.0 | 0.0 |
| 1 | ENSMUSG00000035804 | 824.856750 | 16.893425 | 0.0 | 0.0 |
| 2 | ENSMUSG00000041681 | 824.532349 | 16.914841 | 0.0 | 0.0 |
| 3 | ENSMUSG00000027419 | 419.103363 | 16.480017 | 0.0 | 0.0 |
| 4 | ENSMUSG00000021194 | 391.475525 | 16.594629 | 0.0 | 0.0 |
| ... | ... | ... | ... | ... | ... |
| 17979 | ENSMUSG00000026728 | -392.494598 | -8.722573 | 0.0 | 0.0 |
| 17980 | ENSMUSG00000032231 | -401.135620 | -8.877570 | 0.0 | 0.0 |
| 17981 | ENSMUSG00000030220 | -407.801300 | -8.635771 | 0.0 | 0.0 |
| 17982 | ENSMUSG00000006519 | -470.721527 | -8.405920 | 0.0 | 0.0 |
| 17983 | ENSMUSG00000063229 | -476.040161 | -8.667871 | 0.0 | 0.0 |
17984 rows × 5 columns
In [23]:
#Visualize gene expression of top marker for type B pancreatic cell
scanpy.pl.umap(tm_age, use_raw = False, color = ['ENSMUSG00000000215']) #INS2
#Color by cell type of interest
scanpy.pl.umap(tm_age, color=["cell_type"], groups=["type B pancreatic cell"], show=False)
Out[23]:
<Axes: title={'center': 'cell_type'}, xlabel='UMAP1', ylabel='UMAP2'>
In [24]:
#Visualize gene expression of 2nd and 3rd marker for type B pancreatic cell
scanpy.pl.umap(tm_age, use_raw = False, color = ['ENSMUSG00000035804']) #INS1
scanpy.pl.umap(tm_age, use_raw = False, color = ['ENSMUSG00000041681']) #IAPP